code: def get_parser():
      parser = argparse.ArgumentParser(
          description="PyTorch CIFAR10 Training"
      )
      parser.add_argument(
          "--model",
          default="resnet",
          type=str,
          help="model",
          choices=["resnet", "densenet"],
      )
      parser.add_argument(
          "--optim",
          default="sgd",
          type=str,
          help="optimizer",
          choices=[
              "sgd",
              "adagrad",
              "adam",
              "amsgrad",
              "adabound",
              "amsbound",
          ],
      )
      parser.add_argument(
          "--lr", default=0.1, type=float, help="learning rate"
      )
      parser.add_argument(
          "--final_lr",
          default=0.1,
          type=float,
          help="final learning rate of AdaBound",
      )
      parser.add_argument(
          "--gamma",
          default=1e-3,
          type=float,
          help="convergence speed term of AdaBound",
      )
      parser.add_argument(
          "--momentum", default=0.9, type=float, help="momentum term"
      )
      parser.add_argument(
          "--beta1",
          default=0.9,
          type=float,
          help="Adam coefficients beta_1",
      )
      parser.add_argument(
          "--beta2",
          default=0.999,
          type=float,
          help="Adam coefficients beta_2",
      )
      parser.add_argument(
          "--resume",
          "-r",
          action="store_true",
          help="resume from checkpoint",
      )
      parser.add_argument(
          "--weight_decay",
          default=5e-4,
          type=float,
          help="weight decay for optimizers",
      )
      return parser
  
file_path: AdaBound/demos/cifar10/main.py
imports: from __future__ import print_function
  import torch.optim
  import torch.backends.cudnn
  import torchvision
  import torchvision.transforms
  import os
  import argparse
  from models import *
  from adabound import AdaBound
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser